<![CDATA[Respiratory diseases are one of the health disorders whose prevalence continues to increase and require rapid and accurate diagnosis to support effective medical treatment. This study aims to develop an expert system for diagnosing respiratory diseases using the forward chaining method. This method was chosen for its ability to perform data-driven reasoning, starting from the facts of the symptoms experienced by the patient, which then trigger certain rules to produce a diagnostic conclusion. The system is designed with a knowledge base containing validated data on symptoms and types of respiratory diseases, as well as an inference engine to process diagnostic rules. The system is implemented using a web-based programming language with database integration that stores information on symptoms, diseases, and reasoning rules. Test results show that the system is capable of providing quick and accurate initial diagnoses based on the symptom data entered, and can serve as a tool for medical professionals and the public in detecting respiratory diseases early. This research is expected to contribute to the development of artificial intelligence-based health technology that supports more effective and efficient medical services.]]>
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